A Gold Standard to Measure Relative Linguistic Complexity with a Grounded Language Learning Model

Leonor Becerra-Bonache, Henning Christiansen, M. Dolores Jiménez-López


Abstract
This paper focuses on linguistic complexity from a relative perspective. It presents a grounded language learning system that can be used to study linguistic complexity from a developmental point of view and introduces a tool for generating a gold standard in order to evaluate the performance of the learning system. In general, researchers agree that it is more feasible to approach complexity from an objective or theory-oriented viewpoint than from a subjective or user-related point of view. Studies that have adopted a relative complexity approach have showed some preferences for L2 learners. In this paper, we try to show that computational models of the process of language acquisition may be an important tool to consider children and the process of first language acquisition as suitable candidates for evaluating the complexity of languages.
Anthology ID:
W18-4601
Volume:
Proceedings of the Workshop on Linguistic Complexity and Natural Language Processing
Month:
August
Year:
2018
Address:
Santa Fe, New-Mexico
Venue:
WS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
1–9
Language:
URL:
https://aclanthology.org/W18-4601
DOI:
Bibkey:
Cite (ACL):
Leonor Becerra-Bonache, Henning Christiansen, and M. Dolores Jiménez-López. 2018. A Gold Standard to Measure Relative Linguistic Complexity with a Grounded Language Learning Model. In Proceedings of the Workshop on Linguistic Complexity and Natural Language Processing, pages 1–9, Santa Fe, New-Mexico. Association for Computational Linguistics.
Cite (Informal):
A Gold Standard to Measure Relative Linguistic Complexity with a Grounded Language Learning Model (Becerra-Bonache et al., 2018)
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PDF:
https://aclanthology.org/W18-4601.pdf